Deep Learning with Logical Constraints
Artificial Intelligence
2023-06-21 v1 Machine Learning
Logic in Computer Science
Abstract
In recent years, there has been an increasing interest in exploiting logically specified background knowledge in order to obtain neural models (i) with a better performance, (ii) able to learn from less data, and/or (iii) guaranteed to be compliant with the background knowledge itself, e.g., for safety-critical applications. In this survey, we retrace such works and categorize them based on (i) the logical language that they use to express the background knowledge and (ii) the goals that they achieve.
Cite
@article{arxiv.2205.00523,
title = {Deep Learning with Logical Constraints},
author = {Eleonora Giunchiglia and Mihaela Catalina Stoian and Thomas Lukasiewicz},
journal= {arXiv preprint arXiv:2205.00523},
year = {2023}
}
Comments
Survey paper. IJCAI 2022